[1] Zhang L, Zhang F, Hu Y. A Two-phase Flight Data Feature Selection Method Using both Filter and Wrapper[C]// IEEE International Conference on Systems, Man, and Cybernetics, 1999. IEEE Smc '99 Conference Proceedings. IEEE, 1999:132-136 vol.2.
[2] 姚旭, 王晓丹, 张玉玺,等. 特征选择方法综述[J]. 控制与决策, , 27(2):161-166.
By, Yao Xu,Wang Xiaodan, Zhang Yuxi, et. A review of feature selection methods [J]. Control and decision, , 27 (2): 161-166.
[3] Zhang Y, Gong D, Hu Y, et al. Feature selection algorithm based on bare bones particle swarm optimization[J]. Neurocomputing, , 148(1):150-157.
[4] Bolón-Canedo V, Sánchez-Maroño N, Alonso-Betanzos A. Feature selection for high-dimensional data[J]. Progress in Artificial Intelligence, , 5(2):65-75.
[5] Apolloni J, Alba E. Two hybrid wrapper-filter feature selection algorithms applied to high-dimensional microarray experiments[M]. Elsevier Science Publishers B. V. .
[6] Solorio-Fernández S, Carrasco-Ochoa J A, Martínez-Trinidad J F. A new hybrid filter–wrapper feature selection method for clustering based on ranking[J]. Neurocomputing, , 214:866-880.
[7] 赵荣珍, 李坤杰, 邓林峰. 基于ReliefF和遗传算法的故障特征筛选方法[C]// 全国设备监测诊断与维护学术会议、全国设备故障诊断学术会议暨全国设备诊断工程会议. .
Zhao Rongzhen, Li Kunjie, Deng Linfeng. Fault feature screening method based on Relieff and genetic algorithm [c]//National equipment monitoring and diagnosis and maintenance academic conference, national conference on Equipment Fault diagnosis and National Equipment Diagnostic Engineering Conference. .
[8] 何涛, 胡洁, 夏鹏,等. 基于ReliefF算法与遗传算法的肌电信号特征选择[J].上海交通大学学报,, 50(2):204-208..
He Tao, Hujie, Xia Peng, et. EMG signal Feature selection based on Relieff algorithm and genetic algorithm [J]. Journal of Shanghai Jiaotong University, , 50 (2): 204-208.
[9] 肖艳, 姜琦刚, 王斌,等. 基于Relief F和PSO混合特征选择的面向对象土地利用分类[J]. 农业工程学报, , 32(4):211-216.
Xiao Yan, Jiang Qigang, Wang Bin, et al. Object oriented land use classification based on Relief F and PSO hybrid feature selection [J]. Acta agronomy Sinica, , 32 (4): 211-216..
[10] 孙俊. 量子行为粒子群优化算法研究[D]. 江南大学, .
CMa. Research on particle swarm optimization algorithm for quantum behavior [D]. Jiangnan University, .
[11] Yuan Q, Zhou Z, Yang K. Ultrasonic Non-destructiveClassification for Wood Materials Based on ReliefF and PSO-SVM[J]. Journal of Green Science & Technology, .
[12] 霍天龙, 赵荣珍, 胡宝权. 基于熵带法与PSO优化的SVM转子故障诊断[J]. 振动.测试与诊断, , 31(3):279-284.
Huo Tianlong, Zhao Rongzhen, Hu Baoquan. SVM Rotor Fault Diagnosis Based on Entropy Band Method and PSO Optimization [J]. Vibration. Testing and Diagnosis, , 31(3): 279-284.
[13] 张钦礼, 王兢, 王新民. 基于核主成分分析与PSO-SVM的充填管道失效风险性分级评价模型[J]. 黄金科学技术, , 25(3):70-76.
Zhang Qinli, Wang Jing, Wang Xinmin. Based on nuclear principal component analysis and PSO-SVM classification evaluation model of filling pipeline failure risk [J]. gold science technology, , 25 (3): 70-76.
[14] 柳一鸣. 自适应量子行为粒子群算法及其在图像分类中的应用研究[D]. 浙江大学, .
Liu. Adaptive quantum behavior particle swarm optimization and its application in image classification [D]. Zhejiang University, .
[15] 张燕君, 张芳草, 付兴虎,等. 基于QPSO-MLSSVM算法的拉曼光谱检测四组分调和油含量[J]. 光谱学与光谱分析, , 38(5).
Zhang Yanjun, Zhang Cao, Shinghung, et. Determination of four-component blending oil content by Raman spectroscopy based on QPSO-MLSSVM algorithm [J]. Spectroscopy and spectral analysis, , 38 (5).
